1 to 25 of 60 Permanent Amazon Redshift Jobs in England

and analysis. These technologies are crucial for managing vast datasets and performing complex data transformations and aggregations. Cloud Data Management: Implement and oversee cloud-specific data services including AWS Redshift, S3, Google BigQuery, and Google Cloud Storage. Leverage cloud architectures to improve data sharing and interoperability across different business units. Security and Compliance: Ensure all data practices comply with More ❯

anomaly detection, and GenAI-powered automation Support GenAI initiatives through data readiness, synthetic data generation, and prompt engineering. Mandatory Skills: Cloud Platforms:Deep experience with AWS (S3, Lambda, Glue, Redshift) and/or Azure (Data Lake, Synapse). Programming & Scripting:Proficiency in Python, SQL, PySpark etc. ETL/ELT & Streaming:Expertise in technologies like Apache Airflow, Glue, Kafka, Informatica More ❯

based architecture. You will need to have skills and experience in the following: Cloud Data Architecture: Strong knowledge of modern, cloud-based data architecture and tooling (e.g., S3, Glue, Redshift, Athena, Lake Formation, Iceberg/Delta). AWS Platform Build: Demonstrable experience designing and building modern data platforms in AWS. ETL/Orchestration Expertise: Expertise in ETL/ELT More ❯

based architecture. You will need to have skills and experience in the following: Cloud Data Architecture: Strong knowledge of modern, cloud-based data architecture and tooling (e.g., S3, Glue, Redshift, Athena, Lake Formation, Iceberg/Delta). AWS Platform Build: Demonstrable experience designing and building modern data platforms in AWS. ETL/Orchestration Expertise: Expertise in ETL/ELT More ❯

or dbt. Strong SQL skills and experience with cloud platforms (Azure preferred). Solid programming background in Python, Scala, or Java. Knowledge of data warehousing solutions (e.g. Snowflake, BigQuery, Redshift). Strong understanding of data governance, security, and compliance (experience within financial services is a plus). Leadership experience, with the ability to mentor, influence, and set technical direction. More ❯

engineers and support their growth. Implement best practices for data security and compliance. Collaborate with stakeholders and external partners. Skills & Experience: Strong experience with AWS data technologies (e.g., S3, Redshift, Lambda). Proficient in Python, Apache Spark, and SQL. Experience in data warehouse design and data migration projects. Cloud data platform development and deployment. Expertise across data warehouse and More ❯

databases (SQL Server, Oracle, MySQL, NoSQL) to AWS cloud. Proven experience in on-prem to AWS data migration using AWS-native tools such as DMS, Glue, DataSync, Step Functions, Redshift, Athena, Lambda, RDS, EC2, S3 Data Lake, and CloudWatch. Strong knowledge of data extraction, transformation, and loading (ETL) processes, leveraging tools such as Talend, Informatica, Matillion, Pentaho, MuleSoft, Boomi More ❯

scale that to 500 million events per day. You'll be using Kafka for real-time data streaming and AWS to build, optimise and monitor data warehousing solutions in Amazon RedShift, owning and managing AWS based systems to ensure cost effective, secure and high performance data operations. Location/WFH: You can work from home from anywhere in … data engineering skills and experience, having been through multiple end-to-end data pipeline builds You have a deep knowledge of AWS cloud services including: S3, EC2, Lambda, RDS, RedShift, Glue as well as Kinesis, MongoDB and PostgreSQL You have experience of working in environments with high throughput data (millions of events per hour) You have strong Kafka experience More ❯

s Data Governance and Data Classification policies. Maintain data dictionary. Maintain business level data model. Recommending and introducing new technology where needed. Core: Cloud data platforms (e.g. Snowflake, BigQuery, Redshift) Data transformation technology such as DBT Visual Studio Code Python CI automation systems such as Jenkins A git-based source control system such as BitBucket Data Warehouse/Kimball More ❯

Bells Data Governance and Data Classification policies. Maintain data dictionary. Maintain business level data model. Recommending and introducing new technology where needed. Core: Cloud data platforms (e.g. Snowflake, BigQuery, Redshift) Data transformation technology such as DBT Visual Studio Code Python CI automation systems such as Jenkins A git-based source control system such as BitBucket Data Warehouse/Kimball More ❯

with 2+ years in a technical leadership or management role Strong technical proficiency in data modelling, data warehousing, and distributed systems Hands-on experience with cloud data services (AWS Redshift, Glue, EMR or equivalent) Solid programming skills in Python and SQL Familiarity with DevOps practices (CI/CD, Infrastructure as Code - e.g., Terraform) Excellent communication skills with both technical More ❯

. Hands-on experience with data orchestration tools (Airflow, dbt, Dagster, or Prefect). Solid understanding of cloud data platforms (AWS, GCP, or Azure) and data warehousing (Snowflake, BigQuery, Redshift). Experience with streaming technologies (Kafka, Kinesis, or similar). Strong knowledge of data modelling, governance, and architecture best practices . Excellent leadership, communication, and stakeholder management skills. NICE More ❯

logging and monitoring tools, BI and Data Warehousing solutions and ETL and migration technologies. This should be backed with strong cloud-native data engineering skills e.g. AWS RDS, Aurora, Redshift, Kinesis, Glue or Azure CosmosDB, DataFactory, DataWarehouse, SQL DB etc. Proven experience in quality assuring data programmes, including non-functional testing and performance tuning Hands-on experience of modern More ❯

the organisation. What you'll be doing: Design, develop, and maintain scalable data architectures and ETL pipelines Build and manage data models and data warehouse solutions (Airflow, dbt, and Redshift) Write clean, efficient Python and SQL code for data processing and transformation Integrate data from internal and third-party APIs and services Optimise data pipelines for performance, scalability, and More ❯

entertainment company seeking to hire a Data Engineering Manager to play a key role in their data operations and business intelligence initiatives. Key Responsibilities: Design & maintain AWS BI infrastructure (Redshift, S3, EMR) using Terraform and IaC best practices. Develop CI/CD pipelines (Jenkins, GitHub Actions) to automate ETL and Power BI code deployments. Manage environments (Dev, QA, UAT … across AWS services. Monitor performance & costs in AWS, driving optimisation and efficiency. Champion automation & innovation through new tools, frameworks, and cloud-native solutions. Key Skills: AWS Cloud: Expert in Redshift, S3, Lambda, EMR, and IaC (Terraform/CloudFormation); strong understanding of big data architecture and performance optimisation. CI/CD & Automation: Skilled in Jenkins, GitHub Actions, and Python scripting More ❯

leveraging data to improve the OTM users and agents experience. This role would be suited to an individual with a background in Python, SQL, AWS, Looker, PyTorch, Airflow and Redshift/Postgres. The candidate must be able to exhibit proficiency in working with large volumes of data, automating data loads, and the ability to understand end user requirements with … goal of building a solution to provide high quality data processing and analysis as well as building APIs. RESPONSIBILITIES D evelop data pipelines using Python and Airflow Data warehousing (Redshift/Spectrum) Develop data solutions to address business needs Maintain existing reports and improve their performance QUALIFICATIONS Bachelors degree in Computer Science, Data Science, Mathematics, Engineering or equivalent experience … query performance. Strong skills in Python Experience with AWS or GCP Demonstrated experience and responsibility with data, processes, and building ETL pipelines. Experience with cloud data warehouses such as Amazon Redshift, and Google BigQuery. Building visualizations using tools such as Looker studio or equivalent Experience in designing ETL/ELT solutions, preferably using tools like Airflow or AWS More ❯

experience in similar environments is essential. The Skill Requirements: We're looking for candidates with a blend of the following: Strong knowledge of AWS data services (Glue, S3, Lambda, Redshift, etc.) Solid understanding of ETL processes and data pipeline management Proficiency in Python and PySpark Experience working with SQL-based platforms Previous involvement in migrating on-premise solutions to More ❯

path to production Worked with AWS as a cloud platform Extensive hands-on experience with modern data technologies, ETL tools (e.g. Kafka, Flink, DBT etc.) , data storage (e.g. Snowflake, Redshift, etc.) and also IaC ( e.g. Terraform, CloudFormation ) Software development experience with one or more languages (e.g. Python, Java, Scala, Go ) Pragmatic approach to solving problems Nice to have: keen More ❯

and eventual consistency systems using Kafka, .Net, Java, REST APIs, AWS, Terraform and DevOps Nice to have:experience in data pipping and modelling using SQL, DBT, ETL, Data Warehousing, Redshift and Python, and ecommerce and mobile applications background Additional Information Were a community here that cares as much about your life outside work as how you feel when youre More ❯

modelling, zero trust patterns, vulnerability management, incident runbooks. Data & Integration Reference architectures for streaming/batch (Kafka/MSK, Event Hubs, Pub/Sub), data lakes, warehouses (BigQuery, Synapse, Redshift), ETL/ELT. API strategy (APIM/API Gateway/Apigee), messaging (SQS/SNS/Service Bus/PubSub), event‐driven design. Operations & Reliability Observability stack (CloudWatch/ More ❯

junior team members and support the resolution of data/reporting issues. Requirements 4+ years' experience as a Data Engineer or similar role. Strong SQL skills; extensive experience with Amazon Redshift (and ideally MySQL). Experience with data visualisation tools (preferably Amazon QuickSight). Proficient in AWS Glue and Python for ETL. Strong data modelling and dashboard More ❯

Version Control: Git WHAT YOU NEED Essential: 4+ years in Data/Analytics Engineering or BIStrong SQL skills (production-level)DBT experience (essential)Cloud data warehouse experience (BigQuery, Snowflake, Redshift)Data modeling expertiseUser acquisition or marketing analytics backgroundMobile app or gaming industry experience (highly preferred)Strong communication skillsSelf-starter who works autonomouslyDegree in Engineering, Computer Science, Maths, or related More ❯

Data Engineer in a cloud environment, with openness to various data platforms including AWS, Azure, and Google Cloud. Strong knowledge of data services across multiple platforms (e.g., AWS S3, Redshift, Glue, Azure Blob Storage, Google BigQuery). Expertise in data modelling (Dimensional, Data Vault, Enterprise). Experience designing and implementing modern data architectures. Proficiency with integration/orchestration tools More ❯

in SQL and Python. Proven experience in managing complex data estates and developing automated data pipelines. Good understanding of testing principles and deployment processes. Experience with technologies such as Redshift, Airflow, DBT, and AWS. Strong grasp of data modelling, database architecture, and governance principles. Hands-on experience with Git and modern development workflows. Excellent problem-solving skills, resilience, and More ❯

Collaborative, curious, and happy to work in a self-organising, fast-paced environment. Nice-to-Have Skills: Experience with GCP/BigQuery or other cloud data warehouses (e.g., Snowflake, Redshift). Familiarity with data orchestration tools (e.g., Airflow). Experience with data visualisation platforms (such as Preset.io/Apache Superset or other). Exposure to CI/CD pipelines More ❯